Long-form clinical summarization of hospital admissions has real-world significance
because of its potential to help both clinicians and patients. The factual consistency of …

In recent years, machine learning models have rapidly become better at generating clinical
consultation notes; yet, there is little work on how to properly evaluate the generated …

Objective A major source of information available in electronic health record (EHR) systems
are the clinical free text notes documenting patient care. Managing this information is time …

As the phenomenon of knowledge overload becomes more and more obvious, the
automatic summarization technology still needs to break through the bottleneck in order to …

Summarization of clinical narratives is a long-standing research problem. Here, we
introduce the task of hospital-course summarization. Given the documentation authored …

Automated summarization of clinical texts can reduce the burden of medical professionals.“
Discharge summaries” are one promising application of the summarization, because they …

Summarization aims at extracting the salient information from a document and presenting
the extracted information in a condensed form. Most existing methods for extractive text …

To analyze the limitations and the future directions of the extractive summarization
paradigm, this paper proposes an Integer Linear Programming (ILP) formulation to obtain …

We propose a method for evaluating the quality of generated text by asking evaluators to
count facts, and computing precision, recall, f-score, and accuracy from the raw counts. We …

During the patient's hospitalization, the physician must record daily observations of the
patient and summarize them into a brief document called “discharge summary” when the …